Qianwen Li, Zhi Yang, Kaili Chen, Ming Zhao, Hai Long, Yueming Deng, Haoran Hu, Chen Jia, Meiyu Wu, Zhidan Zhao, Huan Zhu, Suqing Zhou, Mingming Zhao, Pengpeng Cao, Shengnan Zhou, Yang Song, Guishao Tang, Juan Liu, Jiao Jiang, Wei Liao, Wenhui Zhou, Bingyi Yang, Feng Xiong, Suhan Zhang, Xiaofei Gao, Yiqun Jiang, Wei Zhang, Bo Zhang, Yan-Ling He, Liwei Ran, Chunlei Zhang, Wenting Wu, Quzong Suolang, Hanhuan Luo, Xiaojing Kang, Caoying Wu, Hongzhong Jin, Lei Chen, Qing Guo, Guangji Gui, Shanshan Li, Henan Si, Shuping Guo, Hong-Ye Liu, Xiguang Liu, Guo-Zhang Ma, Danqi Deng, Limei Yuan, Jianyun Lu, Jinrong Zeng, Xian Jiang, Xiaoyan Lyu, Liuqing Chen, Bin Hu, Juan Tao, Yuhao Liu, Gang Wang, Guannan Zhu, Zhirong Yao, Qianyue Xu, Bin Yang, Yu Wang, Yan Ding, Xianxu Yang, Hu Kai, Haijing Wu, Qianjin Lu
BACKGROUND: Lupus erythematosus (LE) is a spectrum of autoimmune diseases. Due to the complexity of cutaneous LE (CLE), clinical skin image-based artificial intelligence is still experiencing difficulties in distinguishing subtypes of LE. OBJECTIVES: We aim to develop a multimodal deep learning system (MMDLS) for human-AI collaboration in diagnosis of LE subtypes. METHODS: This is a multi-centre study based on 25 institutions across China to assist in diagnosis of LE subtypes, other eight similar skin diseases and healthy subjects...
April 15, 2024: Journal of the European Academy of Dermatology and Venereology: JEADV